No-reference image quality assessment based on SIFT feature points

被引：0

作者：

Duan W. ^{[1
]}

Yan L. ^{[1
]}

机构：

[1] School of Geodesy and Geomatics, Wuhan University, Wuhan

来源：

International Journal of Simulation: Systems, Science and Technology | 2016年 / 17卷 / 17期

关键词：

Feature points; Feature regions; Image quality; K means clustering algorithm; No reference; Objective assessment; SIFT;

D O I：

10.5013/IJSSST.a.17.17.07

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

Image quality assessment is an important research field of image application. A no-reference image assessment method is proposed based on SIFT feature points and the collection of statistical features from a space domain Natural Scene Statistic (NSS) model. The proposed method extracts feature points by the SIFT method, and the feature regions are extracted by K means clustering algorithm. Then features are computed in the feature regions which can reflect the image quality. The quality of the distorted image is expressed as the distance between the quality aware NSS feature model and the MVG fit to the features extracted from the distorted image. The experimental results show that the proposed method is consistent with human subjective perception. © 2016, UK Simulation Society. All rights reserved.

引用

页码：7.1 / 7.5

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